Almost optimal skin detection approach within the Gaussian framework

Youtian Du; Zhongmin Cai; Xiaohong GuanQian Li

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Almost optimal skin detection approach within the Gaussian framework

机译：Almost optimal skin detection approach within the Gaussian framework

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摘要

Skin detection plays an important role in many applications, including face detection, human motion analysis, and objectionable image filtering. We propose a novel skin detection approach named multiple Gaussian models (MGMs). This approach combines multiple single Gaussian models and determines each model in order to maximize the true positive rate (TPR) of skin detection subject to a fixed predefined false positive rate (FPR). We derive the discrete and continuous forms of MGM approaches in the paper. The proposed approach has almost optimal performance for a broad range of FPRs in the Gaussian framework. Moreover, it has low computational costs in skin detection for new image instances. Experimental results show that the MGM approach has better skin detection performance than previous methods within the Gaussian framework.

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来源
《Optical Engineering》 |2012年第2期|027007-1-027007-9|共9页
作者
Youtian Du; Zhongmin Cai; Xiaohong GuanQian Li;
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作者单位

Xi'an Jiaotong University, Ministry of Education Key Laboratory for Intelligent Networks and Network Security, State Key Laboratory for Manufacturing Systems Engineering 710049, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
skin detection; Gaussian framework; receiver operating characteristic curve; pattern recognition; image analysis;

Almost optimal skin detection approach within the Gaussian framework

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